US-derived Pediatric Kidney Length and Volume Percentiles by Age: A Big Data Approach.

Purpose To calculate new pediatric age-specific normative values and percentiles for kidney length and volume through the use of a natural language processing (NLP) model. Materials and Methods In this cross-sectional study, 24 664 US reports from 18 769 children (birth to 18 years) conducted between January 2012 and December 2022 at a tertiary children's hospital in the northeastern United States were analyzed with an NLP model. Anthropometric data from 12 595 children were used to evaluate the effect of sex and body measurements on kidney length and volume through age-adjusted quantile regression models. Age-related percentiles were established after calibration, using the lambda-mu-sigma (LMS) method by age (year), with detailed subcategories for children younger than 1 year. Volume percentiles by body surface area were also generated using the LMS method. Results A total of 24 664 reports from 18 769 children were included (median age, 7 years [IQR, 11 years]; 10 134 female children). Normative value analysis showed that kidney growth was more pronounced in the 1st year of life (1.8-cm increase in length and 16.9-cm3 increase in volume). The large sample size resulted in standard errors that were 10%-30% less than previous normative values. Quantile regression models showed that body surface area was a better predictor of kidney volume than was age (R1 = 0.57 [P < .001] vs 0.48 [P < .001]). Conclusion New LMS percentiles for kidney size were established using data from a large pediatric sample. Keywords: Kidney, Natural Language Processing, Pediatrics, Ultrasound Supplemental material is available for this article. © The Author(s) 2025. Published by the Radiological Society of North America under a CC BY 4.0 license See also the commentary by Sihlahla in this issue.